Tango's Maximized Excess Events Test with Different Weights

DSpace/Manakin Repository

Tango's Maximized Excess Events Test with Different Weights

Citable link to this page

. . . . . .

Title: Tango's Maximized Excess Events Test with Different Weights
Author: Song, Changhong; Kulldorff, Martin

Note: Order does not necessarily reflect citation order of authors.

Citation: Song, Changhong, and Martin Kulldorff. 2005. Tango's maximized excess events test with different weights. International Journal of Health Geographics 4: 32.
Full Text & Related Files:
Abstract: Background Tango's maximized excess events test (MEET) has been shown to have very good statistical power in detecting global disease clustering. A nice feature of this test is that it considers a range of spatial scale parameters, adjusting for the multiple testing. This means that it has good power to detect a wide range of clustering processes. The test depends on the functional form of a weight function, and it is unknown how sensitive the test is to the choice of this weight function and what function provides optimal power for different clustering processes. In this study, we evaluate the performance of the test for a wide range of weight functions.Results The power varies greatly with different choice of weight. Tango's original choice for the weight function works very well. There are also other weight functions that provide good power.Conclusion We recommend the use of Tango's MEET to test global disease clustering, either with the original weight or one of the alternate weights that have good power.
Published Version: doi:10.1186/1476-072X-4-32
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1343587/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:8191184

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters